1.

Record Nr.

UNINA990006415360403321

Autore

Amory, Patrick

Titolo

People and identity in ostrogothic Italy, 489-554 / Patrick Amory

Pubbl/distr/stampa

Cambridge, : Cambridge University Press, 1997

ISBN

0-521-57151-0

Descrizione fisica

XXI, 522 p. : ill. ; 24 cm

Collana

Cambridge studies in medieval life and thought , 4. Series

Disciplina

945.01

Locazione

FGBC

DDR

Collocazione

XXI A 788

DDR-VI C 025.30

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia



2.

Record Nr.

UNINA9910728934203321

Autore

McGibney Daniel P.

Titolo

Applied Linear Regression for Business Analytics with R : A Practical Guide to Data Science with Case Studies / / by Daniel P. McGibney

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023

ISBN

3-031-21480-3

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (286 pages)

Collana

International Series in Operations Research & Management Science, , 2214-7934 ; ; 337

Disciplina

650.0285

Soggetti

Operations research

Regression analysis

Business information services

Business - Data processing

Mathematical statistics - Data processing

Operations Research and Decision Theory

Linear Models and Regression

IT in Business

Business Analytics

Statistics and Computing

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

1. Introduction -- 2. Basic Statistics and Functions using R -- 3. Regression Fundamentals -- 4. Simple Linear Regression -- 5. Multiple Regression -- 6. Estimation Intervals and Analysis of Variance -- 7. Predictor Variable Transformations -- 8. Model Diagnostics -- 9. Variable Selection.

Sommario/riassunto

Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and relevant case studies from the business world, along with clear and concise explanations of the theory, intuition, hands-on examples, and the coding required to employ regression modeling. Each chapter includes



the mathematical formulation and details of regression analysis and provides in-depth practical analysis using the R programming language.